National Survey on the Status of Embryo Freezing for Fertility Preservation in Japan
Bibliographic record
Abstract
PURPOSE: No studies regarding embryo freezing as a technique for preserving fertility among patients with cancer have been conducted in Japan. Hence, we surveyed embryologists working at fertility preservation facilities to investigate the current status of embryo freezing for fertility preservation in patients with cancer in Japan. METHODS: fertilization and embryo transfer with the Japan Society of Obstetrics and Gynecology were surveyed online about their embryo freezing practices. RESULTS: The survey revealed that 352 institutions perform embryo freezing for general assisted reproduction, while only 178 (50.6%) do so for fertility preservation. About 23.0% use different criteria or personnel for cryopreservation based on purpose, 15.2% freeze pronuclear stage embryos, 84.3% freeze cleavage stage embryos, and 92.7% freeze blastocyst stage embryos. All institutions use vitrification, and over 90% follow the manufacturer's protocol for freezing and thawing. CONCLUSIONS: Fertility preservation through embryo freezing is not widely used in Japan, and there is inadequate data on the therapy's current status and results for patients with cancer. Further research is necessary to provide patients with cancer with the opportunity to preserve their fertility without major concerns and ultimately enhance their quality of life after treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".